1. Field
The present disclosure relates generally to biasing amplifier circuits, and more specifically, to biasing amplifier circuits needing constant gain over process and temperature variations for maintaining a constant transconductance (gm) therein.
2. Background
In RF/analog integrated circuits there is often a need for open-loop amplifier circuits that provide a constant gain which does not change over process and temperature variation. For example, LNAs, active filters, trans-impedance amplifiers and RF driver amplifiers all require such circuits.
To achieve constant gain, a bias circuit is needed to bias the amplifier input transistor in order to compensate for process and temperature variations, thus allowing the transistor to maintain a constant transconductance (gm). A standard constant-gm bias circuit, as shown in FIG. 1, relies on the “square law”, characteristic (i.e. Ids being proportional to (Vgs−Vth)2), and produces a constant gm only with a perfect square law characteristic. An amplifier circuit 100 includes an amplifier 104 biased according to a bias circuit 102. However, such a biasing approach is effective only with long-channel metallic oxide semiconductor (MOS) devices that utilize process technologies which follow the square law. However, in nanometer complementary MOS (CMOS) technologies in which many radio frequency (RF) and analog integrated circuits (ICs) are currently implemented, the current (I) to voltage (V) (I-V) characteristics of a MOS transistor, even with long channel length, deviates substantially from the square law characteristic.
For RF amplifiers which require transistors with a high unity current gain cutoff frequency (ft), short-channel transistors must be used whose I-V characteristics no longer follow the square law characteristic and cannot be easily modeled. Therefore, there is a need for a bias circuit that does not rely on the square-law biasing model and hence allows transistors in deep submicron/nanometer CMOS technologies to maintain constant transconductance (gm) over process and temperature variation.